How to Write Data Scientist Resume With Samples

A Brief About Data Scientist & Resume

Every domain has some designation that people aspire for and in order to attain that job position, there are a number of things that they need to perform. When it comes to the field of Data Science that job position is often considered as Data Scientist. To become a Data Scientist one requires a deep understanding of various theoretical and applicative aspects of it. This understanding is attained after long hours of labor that includes reading books, going through tutorials, long discussions with people involved in this field, etc.

While this knowledge is important, there is one more aspect of Data Science-related knowledge which is less discussed i.e. the knowledge of writing a** Data Scientist’s Resume**. A Data Science resume in India or a Data Science resume to target Indian companies requires understanding the job market and the requirement of the companies.

Resume play a very important role in the process of securing a job. A resume allows a candidate to showcase their discipline-related knowledge, past experience, inquisitiveness regarding the job position among other things. This allows the employers or HRs to decide whether the candidate holds those skills that are required for being considered for the job.

As the resume acts as the preliminary screening for any candidate, it can be considered as the ticket for getting into the whole interview process for any job position. Therefore, informed decision making is required while preparing the resume.

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Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Big Data Resume: Complete Guide & Samples [2021]

Thanks to the rapidly piling amounts of Big Data, the job profile of a Big Data Engineer is peaking.

In recent years, there has been such unprecedented growth in the demand for Big Data Engineers that it has become one of the top-ranking jobs in Data Science today. Since numerous companies across different industries are hiring Big Data Engineers, there’s never been a better time than now to build a career in Big Data. However, you must know how to present yourself as different from the others; you need to stand out from the crowd. Read the blog to have a better understanding of the scope of Big Data in India.

And how will you do that?

By designing and crafting a detailed, well-structured, and eye-catching Big Data resume!

When applying for a Big Data job, or rather for the post of a Big Data Engineer, your resume is the first point of contact between you and your potential employer. If your resume impresses an employer, you will be summoned for a personal interview. So, the key is to make sure you have a fantastic resume that can get you job interview calls.

Usually, Hiring Managers have to look at hundreds of resumes, be it for any job profile. However, when it comes to high-profile jobs like that of the Big Data Engineer, you must be able to grab the attention of the Hiring Manager by highlighting your skills, qualifications, certifications, and your willingness to upskill.

Let’s begin the resume-building process with the job description and key roles and responsibilities of a Big Data Engineer.

Table of Contents

• Who is a Big Data Engineer?
• Job responsibilities of a Big Data Engineer
• Primary Responsibilities of a Big Data Engineer
• Skills required for the profile of a Big Data Engineer
• Big Data Engineer – Resume Building
• Specify your contact information and location :
• Specify your educational qualifications
• Write a brief summary of your work experience
• Highlight the tools and technologies you’ve worked with 
• Specify the company names, job titles/profiles, and duration of your work experience 
• Include any and every certification and academic projects you’ve worked on

#big data #big data resume: complete guide & samples #big data resume #big data resume #data science resume #guide

50 Data Science Jobs That Opened Just Last Week

Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

In this article, we list down 50 latest job openings in data science that opened just last week.

(The jobs are sorted according to the years of experience r

1| Data Scientist at IBM

**Location: **Bangalore

Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.

Apply here.

2| Associate Data Scientist at PayPal

**Location: **Chennai

Skills Required: Data mining experience in Python, R, H2O and/or SAS, cross-functional, highly complex data science projects, SQL or SQL-like tools, among others.

Apply here.

3| Data Scientist at Citrix

Location: Bangalore

Skills Required: Data modelling, database architecture, database design, database programming such as SQL, Python, etc., forecasting algorithms, cloud platforms, designing and developing ETL and ELT processes, etc.

Apply here.

4| Data Scientist at PayPal

**Location: **Bangalore

Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.

Apply here.

5| Data Science at Accenture

**Location: **Bibinagar, Telangana

Skills Required: Data science frameworks Jupyter notebook, AWS Sagemaker, querying databases and using statistical computer languages: R, Python, SLQ, statistical and data mining techniques, distributed data/computing tools such as Map/Reduce, Flume, Drill, Hadoop, Hive, Spark, Gurobi, MySQL, among others.

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#careers #data science #data science career #data science jobs #data science news #data scientist #data scientists #data scientists india

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).

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This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Data Science: Advice for Aspiring Data Scientists | Experfy Insights

Around once a month, I get emailed by a student of some type asking how to get into Data Science, I’ve answered it enough that I decided to write it out here so I can link people to it. So if you’re one of those students, welcome!

I’ll segment this into basic advice, which can be found quite easily if you just google ‘how to get into data science’ and advice that is less common, but advice that I’ve found very useful over the years. I’ll start with the latter, and move on to basic advice. Obviously take this with a grain of salt as all advice comes with a bit of survivorship bias.

Less Basic Advice:

1. Find a solid community

2. Apply Data Science to Things you Enjoy

3. Minimize the ‘Clicks to Proof of Competence’

4. Learn Through Research or Entry Level Jobs

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#big data & cloud #data science #data scientist #statistics #aspiring data scientist #advice for aspiring data scientists